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docs: Add Groq API integration to models tutorial notebook #6893

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62 changes: 60 additions & 2 deletions python/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -576,11 +576,69 @@
"source": [
"Read more about the [Semantic Kernel Adapter](../../../reference/python/autogen_ext.models.semantic_kernel.rst)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Groq (experimental)\n",
"\n",
"[Groq](https://groq.com/) provides ultra-fast inference for open-source LLMs through their cloud API. Groq offers an [OpenAI-compatible API](https://console.groq.com/docs/quickstart), so you can use the {py:class}`~autogen_ext.models.openai.OpenAIChatCompletionClient` with Groq's endpoints.\n",
"\n",
"You will need to obtain an [API key](https://console.groq.com/keys) from Groq.\n",
"\n",
"This endpoint supports the following OpenAI client library features:\n",
"* Chat completions\n",
"* Model selection\n",
"* Temperature/sampling\n",
"* Streaming\n",
"* JSON mode\n",
"* Function calling (tools)\n",
"\n",
"**Note**: While some model providers may offer OpenAI-compatible APIs, they may still have minor differences. For example, the `finish_reason` field may be different in the response."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"finish_reason='stop' content='The capital of France is Paris.' usage=RequestUsage(prompt_tokens=17, completion_tokens=8) cached=False logprobs=None thought=None\n"
]
}
],
"source": [
"import os\n",
"from autogen_core.models import UserMessage\n",
"from autogen_ext.models.openai import OpenAIChatCompletionClient\n",
"\n",
"# Create Groq model client\n",
"model_client = OpenAIChatCompletionClient(\n",
" model=\"llama3-8b-8192\", # or other Groq models like \"mixtral-8x7b-32768\"\n",
" base_url=\"https://api.groq.com/openai/v1\",\n",
" # api_key=\"GROQ_API_KEY\", \n",
" model_info={\n",
" \"vision\": False,\n",
" \"function_calling\": True,\n",
" \"json_output\": True,\n",
" \"family\": \"unknown\",\n",
" \"structured_output\": True,\n",
" },\n",
")\n",
"\n",
"response = await model_client.create([UserMessage(content=\"What is the capital of France?\", source=\"user\")])\n",
"print(response)\n",
"await model_client.close()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"display_name": "autogen",
"language": "python",
"name": "python3"
},
Expand All @@ -594,7 +652,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
"version": "3.10.0"
}
},
"nbformat": 4,
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